Overview

Brought to you by YData

Dataset statistics

Number of variables14
Number of observations105
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory11.6 KiB
Average record size in memory113.3 B

Variable types

Numeric12
Text1
Categorical1

Alerts

academic_reputation is highly overall correlated with employer_reputation and 4 other fieldsHigh correlation
citations_per_faculty is highly overall correlated with overall_score and 2 other fieldsHigh correlation
employer_reputation is highly overall correlated with academic_reputation and 3 other fieldsHigh correlation
employment_outcomes is highly overall correlated with academic_reputation and 3 other fieldsHigh correlation
international_faculty_ratio is highly overall correlated with international_students_ratioHigh correlation
international_students_ratio is highly overall correlated with international_faculty_ratioHigh correlation
overall_score is highly overall correlated with academic_reputation and 5 other fieldsHigh correlation
rank is highly overall correlated with academic_reputation and 5 other fieldsHigh correlation
sequence is highly overall correlated with academic_reputation and 5 other fieldsHigh correlation
Fundos (US$) is highly imbalanced (58.5%)Imbalance
sequence is uniformly distributedUniform
rank is uniformly distributedUniform
sequence has unique valuesUnique
university has unique valuesUnique

Reproduction

Analysis started2025-10-02 05:29:13.328946
Analysis finished2025-10-02 05:29:32.738996
Duration19.41 seconds
Software versionydata-profiling vv4.17.0
Download configurationconfig.json

Variables

sequence
Real number (ℝ)

High correlation  Uniform  Unique 

Distinct105
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean52
Minimum0
Maximum104
Zeros1
Zeros (%)1.0%
Negative0
Negative (%)0.0%
Memory size972.0 B
2025-10-02T10:59:32.797315image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile5.2
Q126
median52
Q378
95-th percentile98.8
Maximum104
Range104
Interquartile range (IQR)52

Descriptive statistics

Standard deviation30.454885
Coefficient of variation (CV)0.58567086
Kurtosis-1.2
Mean52
Median Absolute Deviation (MAD)26
Skewness0
Sum5460
Variance927.5
MonotonicityStrictly increasing
2025-10-02T10:59:32.900441image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
01
 
1.0%
11
 
1.0%
21
 
1.0%
31
 
1.0%
41
 
1.0%
51
 
1.0%
61
 
1.0%
71
 
1.0%
81
 
1.0%
91
 
1.0%
Other values (95)95
90.5%
ValueCountFrequency (%)
01
1.0%
11
1.0%
21
1.0%
31
1.0%
41
1.0%
51
1.0%
61
1.0%
71
1.0%
81
1.0%
91
1.0%
ValueCountFrequency (%)
1041
1.0%
1031
1.0%
1021
1.0%
1011
1.0%
1001
1.0%
991
1.0%
981
1.0%
971
1.0%
961
1.0%
951
1.0%

rank
Real number (ℝ)

High correlation  Uniform 

Distinct87
Distinct (%)82.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean52.8
Minimum1
Maximum105
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size972.0 B
2025-10-02T10:59:33.010230image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile6.2
Q126
median53
Q379
95-th percentile99.8
Maximum105
Range104
Interquartile range (IQR)53

Descriptive statistics

Standard deviation30.420578
Coefficient of variation (CV)0.5761473
Kurtosis-1.2049789
Mean52.8
Median Absolute Deviation (MAD)27
Skewness0.0026091692
Sum5544
Variance925.41154
MonotonicityIncreasing
2025-10-02T10:59:33.109642image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
473
 
2.9%
172
 
1.9%
192
 
1.9%
282
 
1.9%
342
 
1.9%
262
 
1.9%
382
 
1.9%
1002
 
1.9%
812
 
1.9%
652
 
1.9%
Other values (77)84
80.0%
ValueCountFrequency (%)
11
1.0%
21
1.0%
31
1.0%
41
1.0%
51
1.0%
61
1.0%
71
1.0%
81
1.0%
91
1.0%
101
1.0%
ValueCountFrequency (%)
1051
1.0%
1041
1.0%
1031
1.0%
1021
1.0%
1002
1.9%
991
1.0%
981
1.0%
971
1.0%
952
1.9%
932
1.9%

university
Text

Unique 

Distinct105
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size972.0 B
2025-10-02T10:59:33.378267image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length59
Median length44
Mean length27.561905
Min length3

Characters and Unicode

Total characters2894
Distinct characters66
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique105 ?
Unique (%)100.0%

Sample

1st rowMassachusetts Institute of Technology (MIT)
2nd rowUniversity of Cambridge
3rd rowUniversity of Oxford
4th rowHarvard University
5th rowStanford University
ValueCountFrequency (%)
university81
21.0%
of52
 
13.5%
the18
 
4.7%
technology10
 
2.6%
institute6
 
1.6%
de6
 
1.6%
kong5
 
1.3%
hong5
 
1.3%
california4
 
1.0%
national4
 
1.0%
Other values (166)195
50.5%
2025-10-02T10:59:33.742557image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
i286
 
9.9%
281
 
9.7%
e232
 
8.0%
n229
 
7.9%
o178
 
6.2%
t156
 
5.4%
s145
 
5.0%
r144
 
5.0%
a115
 
4.0%
y113
 
3.9%
Other values (56)1015
35.1%

Most occurring categories

ValueCountFrequency (%)
(unknown)2894
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
i286
 
9.9%
281
 
9.7%
e232
 
8.0%
n229
 
7.9%
o178
 
6.2%
t156
 
5.4%
s145
 
5.0%
r144
 
5.0%
a115
 
4.0%
y113
 
3.9%
Other values (56)1015
35.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown)2894
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
i286
 
9.9%
281
 
9.7%
e232
 
8.0%
n229
 
7.9%
o178
 
6.2%
t156
 
5.4%
s145
 
5.0%
r144
 
5.0%
a115
 
4.0%
y113
 
3.9%
Other values (56)1015
35.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown)2894
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
i286
 
9.9%
281
 
9.7%
e232
 
8.0%
n229
 
7.9%
o178
 
6.2%
t156
 
5.4%
s145
 
5.0%
r144
 
5.0%
a115
 
4.0%
y113
 
3.9%
Other values (56)1015
35.1%

overall_score
Real number (ℝ)

High correlation 

Distinct87
Distinct (%)82.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean75.01619
Minimum59.4
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size972.0 B
2025-10-02T10:59:33.838072image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum59.4
5-th percentile60.46
Q164.7
median73.4
Q384.5
95-th percentile96.9
Maximum100
Range40.6
Interquartile range (IQR)19.8

Descriptive statistics

Standard deviation11.454501
Coefficient of variation (CV)0.15269372
Kurtosis-0.924964
Mean75.01619
Median Absolute Deviation (MAD)10.3
Skewness0.40046997
Sum7876.7
Variance131.2056
MonotonicityDecreasing
2025-10-02T10:59:33.945708image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
84.53
 
2.9%
76.23
 
2.9%
86.72
 
1.9%
81.52
 
1.9%
79.52
 
1.9%
872
 
1.9%
66.42
 
1.9%
60.42
 
1.9%
612
 
1.9%
68.72
 
1.9%
Other values (77)83
79.0%
ValueCountFrequency (%)
59.41
1.0%
59.71
1.0%
59.91
1.0%
601
1.0%
60.42
1.9%
60.71
1.0%
60.81
1.0%
60.91
1.0%
612
1.9%
61.42
1.9%
ValueCountFrequency (%)
1001
1.0%
99.21
1.0%
98.91
1.0%
98.31
1.0%
98.11
1.0%
97.81
1.0%
93.31
1.0%
92.71
1.0%
92.41
1.0%
90.41
1.0%

academic_reputation
Real number (ℝ)

High correlation 

Distinct90
Distinct (%)85.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean82.724762
Minimum43.4
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size972.0 B
2025-10-02T10:59:34.047611image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum43.4
5-th percentile52.12
Q171.3
median85
Q397.6
95-th percentile100
Maximum100
Range56.6
Interquartile range (IQR)26.3

Descriptive statistics

Standard deviation15.819406
Coefficient of variation (CV)0.1912294
Kurtosis-0.44296644
Mean82.724762
Median Absolute Deviation (MAD)13.1
Skewness-0.76099426
Sum8686.1
Variance250.25361
MonotonicityNot monotonic
2025-10-02T10:59:34.147379image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1008
 
7.6%
98.32
 
1.9%
99.42
 
1.9%
99.12
 
1.9%
98.12
 
1.9%
84.62
 
1.9%
81.22
 
1.9%
69.32
 
1.9%
88.42
 
1.9%
99.51
 
1.0%
Other values (80)80
76.2%
ValueCountFrequency (%)
43.41
1.0%
44.81
1.0%
45.71
1.0%
47.31
1.0%
51.51
1.0%
51.61
1.0%
54.21
1.0%
56.21
1.0%
58.31
1.0%
58.71
1.0%
ValueCountFrequency (%)
1008
7.6%
99.91
 
1.0%
99.81
 
1.0%
99.71
 
1.0%
99.61
 
1.0%
99.51
 
1.0%
99.42
 
1.9%
99.12
 
1.9%
991
 
1.0%
98.81
 
1.0%

employer_reputation
Real number (ℝ)

High correlation 

Distinct89
Distinct (%)84.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean77.487619
Minimum27.3
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size972.0 B
2025-10-02T10:59:34.256023image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum27.3
5-th percentile40
Q159.9
median84.7
Q396.3
95-th percentile99.98
Maximum100
Range72.7
Interquartile range (IQR)36.4

Descriptive statistics

Standard deviation21.561373
Coefficient of variation (CV)0.27825572
Kurtosis-0.72821086
Mean77.487619
Median Absolute Deviation (MAD)13.5
Skewness-0.74865964
Sum8136.2
Variance464.89283
MonotonicityNot monotonic
2025-10-02T10:59:34.361256image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1006
 
5.7%
98.23
 
2.9%
89.12
 
1.9%
962
 
1.9%
95.42
 
1.9%
982
 
1.9%
99.82
 
1.9%
99.12
 
1.9%
96.92
 
1.9%
42.42
 
1.9%
Other values (79)80
76.2%
ValueCountFrequency (%)
27.31
1.0%
27.61
1.0%
30.21
1.0%
30.51
1.0%
36.51
1.0%
39.81
1.0%
40.81
1.0%
42.42
1.9%
42.61
1.0%
44.21
1.0%
ValueCountFrequency (%)
1006
5.7%
99.91
 
1.0%
99.82
 
1.9%
99.61
 
1.0%
99.51
 
1.0%
99.41
 
1.0%
99.12
 
1.9%
98.51
 
1.0%
98.31
 
1.0%
98.23
2.9%

faculty_student_ratio
Real number (ℝ)

Distinct91
Distinct (%)86.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean59.839048
Minimum4.4
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size972.0 B
2025-10-02T10:59:34.465763image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum4.4
5-th percentile9.74
Q134.9
median61.3
Q390.4
95-th percentile100
Maximum100
Range95.6
Interquartile range (IQR)55.5

Descriptive statistics

Standard deviation31.077547
Coefficient of variation (CV)0.5193523
Kurtosis-1.3205163
Mean59.839048
Median Absolute Deviation (MAD)28.6
Skewness-0.17062377
Sum6283.1
Variance965.81394
MonotonicityNot monotonic
2025-10-02T10:59:34.570233image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1009
 
8.6%
99.92
 
1.9%
90.42
 
1.9%
99.82
 
1.9%
37.32
 
1.9%
66.22
 
1.9%
54.72
 
1.9%
98.51
 
1.0%
72.11
 
1.0%
98.41
 
1.0%
Other values (81)81
77.1%
ValueCountFrequency (%)
4.41
1.0%
71
1.0%
7.51
1.0%
8.91
1.0%
91
1.0%
9.61
1.0%
10.31
1.0%
11.81
1.0%
15.31
1.0%
15.41
1.0%
ValueCountFrequency (%)
1009
8.6%
99.92
 
1.9%
99.82
 
1.9%
99.71
 
1.0%
99.31
 
1.0%
98.91
 
1.0%
98.51
 
1.0%
98.41
 
1.0%
98.31
 
1.0%
97.31
 
1.0%

citations_per_faculty
Real number (ℝ)

High correlation 

Distinct89
Distinct (%)84.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean70.589524
Minimum1.7
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size972.0 B
2025-10-02T10:59:34.680423image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum1.7
5-th percentile30.28
Q151.4
median72.4
Q393.5
95-th percentile99.9
Maximum100
Range98.3
Interquartile range (IQR)42.1

Descriptive statistics

Standard deviation25.671385
Coefficient of variation (CV)0.36367131
Kurtosis-0.34406063
Mean70.589524
Median Absolute Deviation (MAD)21.1
Skewness-0.66610363
Sum7411.9
Variance659.01999
MonotonicityNot monotonic
2025-10-02T10:59:34.781984image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1004
 
3.8%
99.94
 
3.8%
98.93
 
2.9%
74.32
 
1.9%
92.32
 
1.9%
93.52
 
1.9%
45.82
 
1.9%
99.12
 
1.9%
68.42
 
1.9%
38.22
 
1.9%
Other values (79)80
76.2%
ValueCountFrequency (%)
1.71
1.0%
2.71
1.0%
4.61
1.0%
11.61
1.0%
26.71
1.0%
29.91
1.0%
31.81
1.0%
32.71
1.0%
36.21
1.0%
36.61
1.0%
ValueCountFrequency (%)
1004
3.8%
99.94
3.8%
99.41
 
1.0%
99.12
1.9%
98.93
2.9%
98.31
 
1.0%
98.11
 
1.0%
981
 
1.0%
97.71
 
1.0%
97.61
 
1.0%

international_faculty_ratio
Real number (ℝ)

High correlation 

Distinct79
Distinct (%)75.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean70.159048
Minimum6
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size972.0 B
2025-10-02T10:59:34.879617image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum6
5-th percentile11.18
Q139.1
median88.9
Q399.1
95-th percentile100
Maximum100
Range94
Interquartile range (IQR)60

Descriptive statistics

Standard deviation33.426261
Coefficient of variation (CV)0.4764355
Kurtosis-1.1713642
Mean70.159048
Median Absolute Deviation (MAD)11.1
Skewness-0.68590223
Sum7366.7
Variance1117.3149
MonotonicityNot monotonic
2025-10-02T10:59:34.980120image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10023
 
21.9%
98.83
 
2.9%
98.22
 
1.9%
962
 
1.9%
99.91
 
1.0%
92.21
 
1.0%
99.11
 
1.0%
81.21
 
1.0%
68.71
 
1.0%
92.91
 
1.0%
Other values (69)69
65.7%
ValueCountFrequency (%)
61
1.0%
8.31
1.0%
9.31
1.0%
9.41
1.0%
10.31
1.0%
11.11
1.0%
11.51
1.0%
13.61
1.0%
14.91
1.0%
16.41
1.0%
ValueCountFrequency (%)
10023
21.9%
99.91
 
1.0%
99.81
 
1.0%
99.51
 
1.0%
99.11
 
1.0%
98.83
 
2.9%
98.71
 
1.0%
98.51
 
1.0%
98.31
 
1.0%
98.22
 
1.9%

international_students_ratio
Real number (ℝ)

High correlation 

Distinct93
Distinct (%)88.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean67.961905
Minimum2.3
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size972.0 B
2025-10-02T10:59:35.086453image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum2.3
5-th percentile11.92
Q145.7
median78.8
Q396.8
95-th percentile100
Maximum100
Range97.7
Interquartile range (IQR)51.1

Descriptive statistics

Standard deviation30.819878
Coefficient of variation (CV)0.45348755
Kurtosis-0.92395614
Mean67.961905
Median Absolute Deviation (MAD)20.7
Skewness-0.64045333
Sum7136
Variance949.86488
MonotonicityNot monotonic
2025-10-02T10:59:35.184725image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10010
 
9.5%
98.22
 
1.9%
91.42
 
1.9%
93.32
 
1.9%
88.21
 
1.0%
51.21
 
1.0%
98.51
 
1.0%
81.91
 
1.0%
63.91
 
1.0%
84.41
 
1.0%
Other values (83)83
79.0%
ValueCountFrequency (%)
2.31
1.0%
2.51
1.0%
2.61
1.0%
3.51
1.0%
111
1.0%
11.61
1.0%
13.21
1.0%
14.51
1.0%
15.71
1.0%
201
1.0%
ValueCountFrequency (%)
10010
9.5%
99.91
 
1.0%
99.81
 
1.0%
99.71
 
1.0%
99.61
 
1.0%
99.51
 
1.0%
99.41
 
1.0%
99.31
 
1.0%
99.11
 
1.0%
991
 
1.0%
Distinct92
Distinct (%)87.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean74.531429
Minimum1.3
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size972.0 B
2025-10-02T10:59:35.283351image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum1.3
5-th percentile20.22
Q158.3
median85.2
Q395.5
95-th percentile99.9
Maximum100
Range98.7
Interquartile range (IQR)37.2

Descriptive statistics

Standard deviation27.030529
Coefficient of variation (CV)0.36267289
Kurtosis0.12091158
Mean74.531429
Median Absolute Deviation (MAD)11.5
Skewness-1.1402141
Sum7825.8
Variance730.64948
MonotonicityNot monotonic
2025-10-02T10:59:35.386907image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1005
 
4.8%
903
 
2.9%
962
 
1.9%
99.92
 
1.9%
86.22
 
1.9%
33.22
 
1.9%
98.72
 
1.9%
95.52
 
1.9%
89.72
 
1.9%
96.71
 
1.0%
Other values (82)82
78.1%
ValueCountFrequency (%)
1.31
1.0%
5.31
1.0%
8.91
1.0%
10.61
1.0%
17.41
1.0%
19.61
1.0%
22.71
1.0%
22.81
1.0%
251
1.0%
26.71
1.0%
ValueCountFrequency (%)
1005
4.8%
99.92
 
1.9%
99.71
 
1.0%
99.61
 
1.0%
99.21
 
1.0%
991
 
1.0%
98.72
 
1.9%
98.41
 
1.0%
98.11
 
1.0%
97.61
 
1.0%

employment_outcomes
Real number (ℝ)

High correlation 

Distinct88
Distinct (%)83.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean63.664762
Minimum13.4
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size972.0 B
2025-10-02T10:59:35.485993image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum13.4
5-th percentile22
Q139.6
median66
Q392.5
95-th percentile100
Maximum100
Range86.6
Interquartile range (IQR)52.9

Descriptive statistics

Standard deviation27.323877
Coefficient of variation (CV)0.42918368
Kurtosis-1.3288339
Mean63.664762
Median Absolute Deviation (MAD)26.5
Skewness-0.10075882
Sum6684.8
Variance746.59423
MonotonicityNot monotonic
2025-10-02T10:59:35.595534image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1008
 
7.6%
663
 
2.9%
82.22
 
1.9%
68.42
 
1.9%
99.72
 
1.9%
702
 
1.9%
94.32
 
1.9%
99.92
 
1.9%
29.52
 
1.9%
70.62
 
1.9%
Other values (78)78
74.3%
ValueCountFrequency (%)
13.41
1.0%
17.71
1.0%
19.41
1.0%
19.71
1.0%
19.81
1.0%
21.91
1.0%
22.41
1.0%
23.41
1.0%
24.41
1.0%
24.91
1.0%
ValueCountFrequency (%)
1008
7.6%
99.92
 
1.9%
99.81
 
1.0%
99.72
 
1.9%
99.51
 
1.0%
98.71
 
1.0%
98.61
 
1.0%
98.31
 
1.0%
981
 
1.0%
97.71
 
1.0%

sustainability
Real number (ℝ)

Distinct87
Distinct (%)82.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean78.722857
Minimum13.4
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size972.0 B
2025-10-02T10:59:35.696928image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum13.4
5-th percentile32.42
Q171.8
median83.7
Q395.1
95-th percentile99.7
Maximum100
Range86.6
Interquartile range (IQR)23.3

Descriptive statistics

Standard deviation21.72881
Coefficient of variation (CV)0.27601654
Kurtosis1.4881139
Mean78.722857
Median Absolute Deviation (MAD)11.5
Skewness-1.4118045
Sum8265.9
Variance472.1412
MonotonicityNot monotonic
2025-10-02T10:59:35.798594image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
99.93
 
2.9%
99.73
 
2.9%
97.32
 
1.9%
88.12
 
1.9%
88.42
 
1.9%
97.82
 
1.9%
94.42
 
1.9%
94.22
 
1.9%
80.42
 
1.9%
99.62
 
1.9%
Other values (77)83
79.0%
ValueCountFrequency (%)
13.41
1.0%
14.21
1.0%
16.91
1.0%
181
1.0%
18.81
1.0%
311
1.0%
38.11
1.0%
41.41
1.0%
42.31
1.0%
42.61
1.0%
ValueCountFrequency (%)
1001
 
1.0%
99.93
2.9%
99.73
2.9%
99.62
1.9%
99.51
 
1.0%
99.41
 
1.0%
99.21
 
1.0%
99.11
 
1.0%
98.41
 
1.0%
98.31
 
1.0%

Fundos (US$)
Categorical

Imbalance 

Distinct27
Distinct (%)25.7%
Missing0
Missing (%)0.0%
Memory size972.0 B
0
79 
7.8
 
1
9.2
 
1
6.3
 
1
6.2
 
1
Other values (22)
22 

Length

Max length3
Median length1
Mean length1.4761905
Min length1

Characters and Unicode

Total characters155
Distinct characters12
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique26 ?
Unique (%)24.8%

Sample

1st row9.2
2nd row7.8
3rd row6.7
4th row6.3
5th row6.2

Common Values

ValueCountFrequency (%)
079
75.2%
7.81
 
1.0%
9.21
 
1.0%
6.31
 
1.0%
6.21
 
1.0%
6.11
 
1.0%
5.91
 
1.0%
5.71
 
1.0%
5.61
 
1.0%
6,71
 
1.0%
Other values (17)17
 
16.2%

Length

2025-10-02T10:59:35.891487image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
079
75.2%
7.81
 
1.0%
9.21
 
1.0%
6.31
 
1.0%
6.21
 
1.0%
6.11
 
1.0%
5.91
 
1.0%
5.71
 
1.0%
5.61
 
1.0%
6,71
 
1.0%
Other values (17)17
 
16.2%

Most occurring characters

ValueCountFrequency (%)
079
51.0%
,16
 
10.3%
513
 
8.4%
611
 
7.1%
.9
 
5.8%
76
 
3.9%
45
 
3.2%
94
 
2.6%
24
 
2.6%
33
 
1.9%
Other values (2)5
 
3.2%

Most occurring categories

ValueCountFrequency (%)
(unknown)155
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
079
51.0%
,16
 
10.3%
513
 
8.4%
611
 
7.1%
.9
 
5.8%
76
 
3.9%
45
 
3.2%
94
 
2.6%
24
 
2.6%
33
 
1.9%
Other values (2)5
 
3.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown)155
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
079
51.0%
,16
 
10.3%
513
 
8.4%
611
 
7.1%
.9
 
5.8%
76
 
3.9%
45
 
3.2%
94
 
2.6%
24
 
2.6%
33
 
1.9%
Other values (2)5
 
3.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown)155
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
079
51.0%
,16
 
10.3%
513
 
8.4%
611
 
7.1%
.9
 
5.8%
76
 
3.9%
45
 
3.2%
94
 
2.6%
24
 
2.6%
33
 
1.9%
Other values (2)5
 
3.2%

Interactions

2025-10-02T10:59:31.777954image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
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2025-10-02T10:59:32.400409image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-02T10:59:15.071139image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-02T10:59:16.649766image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-02T10:59:18.415828image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-02T10:59:23.259154image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-02T10:59:26.885649image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-02T10:59:27.663358image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-02T10:59:28.441032image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-02T10:59:29.191485image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-02T10:59:29.963364image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-02T10:59:30.735822image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-02T10:59:31.474238image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-02T10:59:32.460071image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-02T10:59:15.197563image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-02T10:59:16.774627image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-02T10:59:18.562705image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-02T10:59:23.904437image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-02T10:59:26.951958image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-02T10:59:27.723678image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-02T10:59:28.501306image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-02T10:59:29.251127image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-02T10:59:30.025288image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-02T10:59:30.796822image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-02T10:59:31.541106image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Correlations

2025-10-02T10:59:35.968226image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Fundos (US$)academic_reputationcitations_per_facultyemployer_reputationemployment_outcomesfaculty_student_ratiointernational_faculty_ratiointernational_research_networkinternational_students_ratiooverall_scoreranksequencesustainability
Fundos (US$)1.0000.0000.0000.0000.0000.0000.1220.0000.0000.4220.1440.1440.000
academic_reputation0.0001.0000.1750.6180.6180.289-0.0790.170-0.1100.770-0.771-0.7690.300
citations_per_faculty0.0000.1751.000-0.0280.1490.0240.360-0.0870.1360.517-0.517-0.518-0.133
employer_reputation0.0000.618-0.0281.0000.4060.397-0.2370.075-0.1190.538-0.539-0.5380.204
employment_outcomes0.0000.6180.1490.4061.0000.240-0.0170.085-0.0340.590-0.591-0.5900.443
faculty_student_ratio0.0000.2890.0240.3970.2401.000-0.015-0.054-0.0190.403-0.402-0.402-0.068
international_faculty_ratio0.122-0.0790.360-0.237-0.017-0.0151.0000.1930.7210.302-0.302-0.3030.235
international_research_network0.0000.170-0.0870.0750.085-0.0540.1931.0000.3150.251-0.250-0.2500.418
international_students_ratio0.000-0.1100.136-0.119-0.034-0.0190.7210.3151.0000.260-0.260-0.2610.275
overall_score0.4220.7700.5170.5380.5900.4030.3020.2510.2601.000-1.000-1.0000.317
rank0.144-0.771-0.517-0.539-0.591-0.402-0.302-0.250-0.260-1.0001.0001.000-0.318
sequence0.144-0.769-0.518-0.538-0.590-0.402-0.303-0.250-0.261-1.0001.0001.000-0.317
sustainability0.0000.300-0.1330.2040.443-0.0680.2350.4180.2750.317-0.318-0.3171.000

Missing values

2025-10-02T10:59:32.569075image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
A simple visualization of nullity by column.
2025-10-02T10:59:32.675881image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

sequencerankuniversityoverall_scoreacademic_reputationemployer_reputationfaculty_student_ratiocitations_per_facultyinternational_faculty_ratiointernational_students_ratiointernational_research_networkemployment_outcomessustainabilityFundos (US$)
001Massachusetts Institute of Technology (MIT)100.0100.0100.0100.0100.0100.088.294.3100.095.29.2
112University of Cambridge99.2100.0100.0100.092.3100.095.899.9100.097.37.8
223University of Oxford98.9100.0100.0100.090.698.298.2100.0100.097.86.7
334Harvard University98.3100.0100.098.3100.084.666.8100.0100.096.76.3
445Stanford University98.1100.0100.0100.099.999.951.295.8100.094.46.2
556Imperial College London97.898.399.498.594.0100.0100.096.783.094.46.1
667ETH Zurich93.398.883.672.198.9100.098.596.079.188.45.9
778National University of Singapore (NUS)92.799.488.676.593.2100.081.976.3100.088.15.7
889UCL92.499.597.998.474.399.1100.0100.051.692.55.6
9910University of California, Berkeley (UCB)90.4100.0100.020.599.992.263.992.498.7100.06,7
sequencerankuniversityoverall_scoreacademic_reputationemployer_reputationfaculty_student_ratiocitations_per_facultyinternational_faculty_ratiointernational_students_ratiointernational_research_networkemployment_outcomessustainabilityFundos (US$)
959595University of St Andrews61.047.367.264.957.798.7100.051.122.492.10
969697Georgia Institute of Technology60.967.485.115.367.138.865.433.241.770.40
979798Freie Universitaet Berlin60.880.851.04.471.462.843.684.921.960.10
989899Purdue University60.763.981.210.368.441.545.875.453.467.40
9999100Pohang University of Science And Technology (POSTECH)60.451.675.999.998.333.82.61.313.416.90
100100100University of Nottingham60.460.772.132.246.590.075.298.424.480.00
101101102University of Wisconsin-Madison60.080.247.861.337.430.922.883.673.183.70
102102103Pontificia Universidad Católica de Chile (UC)59.992.999.520.611.616.43.556.876.391.30
103103104The University of Sheffield59.758.752.354.746.984.097.596.124.976.30
104104105Uppsala University59.462.730.547.745.698.382.495.558.299.40